1
|
Cifani P, Kentsis A. Quantitative Cell Proteomic Atlas: Pathway-Scale Targeted Mass Spectrometry for High-Resolution Functional Profiling of Cell Signaling. J Proteome Res 2022; 21:2535-2544. [PMID: 36154077 PMCID: PMC10494574 DOI: 10.1021/acs.jproteome.2c00223] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
In spite of extensive studies of cellular signaling, many fundamental processes such as pathway integration, cross-talk, and feedback remain poorly understood. To enable integrated and quantitative measurements of cellular biochemical activities, we have developed the Quantitative Cell Proteomics Atlas (QCPA). QCPA consists of panels of targeted mass spectrometry assays to determine the abundance and stoichiometry of regulatory post-translational modifications of sentinel proteins from most known physiologic and pathogenic signaling pathways in human cells. QCPA currently profiles 1 913 peptides from 469 effectors of cell surface signaling, apoptosis, stress response, gene expression, quiescence, and proliferation. For each protein, QCPA includes triplets of isotopically labeled peptides covering known post-translational regulatory sites to determine their stoichiometries and unmodified protein regions to measure total protein abundance. The QCPA framework incorporates analytes to control for technical variability of sample preparation and mass spectrometric analysis, including TrypQuant, a synthetic substrate for accurate quantification of proteolysis efficiency for proteins containing chemically modified residues. The ability to precisely and accurately quantify most known signaling pathways should enable improved chemoproteomic approaches for the comprehensive analysis of cell signaling and clinical proteomics of diagnostic specimens. QCPA is openly available at https://qcpa.mskcc.org.
Collapse
Affiliation(s)
- Paolo Cifani
- Molecular Pharmacology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, 10065 USA
| | - Alex Kentsis
- Molecular Pharmacology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, 10065 USA
- Tow Center for Developmental Oncology, Department of Pediatrics, Memorial Sloan Kettering Cancer Center, NY, 10065 USA
- Departments of Pediatrics, Pharmacology, and Physiology & Biophysics, Weill Medical College of Cornell University, NY, 10065 USA
| |
Collapse
|
2
|
Kennedy J, Whiteaker JR, Ivey RG, Burian A, Chowdhury S, Tsai CF, Liu T, Lin C, Murillo OD, Lundeen RA, Jones LA, Gafken PR, Longton G, Rodland KD, Skates SJ, Landua J, Wang P, Lewis MT, Paulovich AG. Internal Standard Triggered-Parallel Reaction Monitoring Mass Spectrometry Enables Multiplexed Quantification of Candidate Biomarkers in Plasma. Anal Chem 2022; 94:9540-9547. [PMID: 35767427 PMCID: PMC9280723 DOI: 10.1021/acs.analchem.1c04382] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Despite advances in proteomic technologies, clinical translation of plasma biomarkers remains low, partly due to a major bottleneck between the discovery of candidate biomarkers and costly clinical validation studies. Due to a dearth of multiplexable assays, generally only a few candidate biomarkers are tested, and the validation success rate is accordingly low. Previously, mass spectrometry-based approaches have been used to fill this gap but feature poor quantitative performance and were generally limited to hundreds of proteins. Here, we demonstrate the capability of an internal standard triggered-parallel reaction monitoring (IS-PRM) assay to greatly expand the numbers of candidates that can be tested with improved quantitative performance. The assay couples immunodepletion and fractionation with IS-PRM and was developed and implemented in human plasma to quantify 5176 peptides representing 1314 breast cancer biomarker candidates. Characterization of the IS-PRM assay demonstrated the precision (median % CV of 7.7%), linearity (median R2 > 0.999 over 4 orders of magnitude), and sensitivity (median LLOQ < 1 fmol, approximately) to enable rank-ordering of candidate biomarkers for validation studies. Using three plasma pools from breast cancer patients and three control pools, 893 proteins were quantified, of which 162 candidate biomarkers were verified in at least one of the cancer pools and 22 were verified in all three cancer pools. The assay greatly expands capabilities for quantification of large numbers of proteins and is well suited for prioritization of viable candidate biomarkers.
Collapse
Affiliation(s)
- Jacob
J. Kennedy
- Clinical
Research Division, Fred Hutchinson Cancer
Research Center, Seattle, Washington 98109, United States
| | - Jeffrey R. Whiteaker
- Clinical
Research Division, Fred Hutchinson Cancer
Research Center, Seattle, Washington 98109, United States
| | - Richard G. Ivey
- Clinical
Research Division, Fred Hutchinson Cancer
Research Center, Seattle, Washington 98109, United States
| | - Aura Burian
- Clinical
Research Division, Fred Hutchinson Cancer
Research Center, Seattle, Washington 98109, United States
| | - Shrabanti Chowdhury
- Department
of Genetics and Genomic Sciences and Icahn Institute for Data Science
and Genomic Technology, Icahn School of
Medicine at Mount Sinai, New York, New York 10029, United States
| | - Chia-Feng Tsai
- Biological
Sciences Division, Pacific Northwest National
Laboratory, Richland, Washington 99352, United States
| | - Tao Liu
- Biological
Sciences Division, Pacific Northwest National
Laboratory, Richland, Washington 99352, United States
| | - ChenWei Lin
- Clinical
Research Division, Fred Hutchinson Cancer
Research Center, Seattle, Washington 98109, United States
| | - Oscar D. Murillo
- Clinical
Research Division, Fred Hutchinson Cancer
Research Center, Seattle, Washington 98109, United States
| | - Rachel A. Lundeen
- Clinical
Research Division, Fred Hutchinson Cancer
Research Center, Seattle, Washington 98109, United States
| | - Lisa A. Jones
- Proteomics
and Metabolomics Shared Resources, Fred
Hutchinson Cancer Research Center, Seattle, Washington 98109, United States
| | - Philip R. Gafken
- Proteomics
and Metabolomics Shared Resources, Fred
Hutchinson Cancer Research Center, Seattle, Washington 98109, United States
| | - Gary Longton
- Public
Health Sciences Division, Fred Hutchinson
Cancer Research Center, Seattle, Washington 98109, United States
| | - Karin D. Rodland
- Biological
Sciences Division, Pacific Northwest National
Laboratory, Richland, Washington 99352, United States
| | - Steven J. Skates
- MGH
Biostatistics Center, Harvard Medical School, Boston, Massachusetts 02114, United States
| | - John Landua
- Lester
and Sue Smith Breast Center, Baylor College
of Medicine, Houston, Texas 77030, United States
| | - Pei Wang
- Department
of Genetics and Genomic Sciences, Mount
Sinai Hospital, New York, New York 10065, United States
| | - Michael T. Lewis
- Lester
and Sue Smith Breast Center, Baylor College
of Medicine, Houston, Texas 77030, United States
| | - Amanda G. Paulovich
- Clinical
Research Division, Fred Hutchinson Cancer
Research Center, Seattle, Washington 98109, United States,Phone: 206-667-1912. . Fax: 206-667-2277
| |
Collapse
|